Performance measurements of monocrystalline silicon PV modules in South-eastern Italy

Congedo, Paolo Maria; Malvoni, Maria; Mele, Mahmuda Akter; Giorgi, Maria Grazia De

doi:10.1016/j.enconman.2012.12.017

Cited by 131 publications

(76 citation statements)

References 11 publications

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“…The results show that the NWP time series assume higher values of effectiveness factor for short and very short prediction lengths: in particular temperature for the component d 1 …”

Section: Discussionmentioning

confidence: 93%

“…For the component a 3 all input variables show the same behavior, in accordance with its characteristic to hold a generic trend of the original signal. A negligible influence of the measured power produced on ANN training is evident for the detail components, while NWP time series assume higher significant values, compared to a 3 behavior, for short and very short prediction time lengths: in particular, the temperature for the component d 1 …”

Section: In P U T Ve Ct O R I L S -S V M In P U T Ve Ct O R I a N N Imentioning

confidence: 99%

“…The study of the methodologies for the optimal management of renewable power systems constitutes an important area of research for the efficient and profitable use of these sources [1,2]. This issue is of particular importance for wind power [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)

et al. 2014

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A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP). A comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain. The performances of Least-Squares Support Vector Machine (LS-SVM) with Wavelet Decomposition (WD) were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN)-based methods. It is acknowledged that hybrid methods based on LS-SVM with WD mostly outperform other methods. A decomposition of the commonly known root mean square error was beneficial for a better understanding of the origin of the differences between prediction and measurement and to compare the accuracy of the different models. A sensitivity analysis was also carried out in order to underline the impact that each input had in the network training process for ANN. In the case of ANN with the WD technique, the sensitivity analysis was repeated on each component obtained by the decomposition.

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“…The results show that the NWP time series assume higher values of effectiveness factor for short and very short prediction lengths: in particular temperature for the component d 1 …”

Section: Discussionmentioning

confidence: 93%

Section: In P U T Ve Ct O R I L S -S V M In P U T Ve Ct O R I a N N Imentioning

confidence: 99%

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Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)

et al. 2014

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“…A recent study is that of Congedo et al [23], which focuses on the influence of climatic characteristics on a 960 kWp mc-Si PV power plant, divided in two subfields with different tilt angles and different nominal powers (606.6 kWp and 353.3 kWp) in south-eastern Italy. The results revealed that the performance ratio varies between 79% and 86.5% for the period of March to October 2012.…”

Section: Introductionmentioning

confidence: 99%

Comparative performance investigation of mono- and poly-crystalline silicon photovoltaic modules for use in grid-connected photovoltaic systems in dry climates

2015

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“…PV systems performance is strongly dependent on weather conditions [17][18][19][20]. Therefore, for the PV system at rooftop of Mineirão Football Stadium, four meteorological/solarimetric stations that measure global irradiance in horizontal plane (GHI) using a Kipp & Zonen pyranometers model CMP 21; ambient temperature/humidity using a PT-100 and humidity sensors; and wind speed/direction using ultrasonic anemometers Lufft, model 200A were installed.…”

Section: Solar Resource Characterization-method Results and Discussionmentioning

confidence: 99%

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

et al. 2017

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This paper presents results of one-year monitoring of AC side electrical parameters and the characterization of local solar radiation at the biggest rooftop PV Power Plant, with an installed capacity of 1.42 MWp, mounted at Mineirão Football Stadium in Brazil. This stadium is one of the sport facilities that hosted 2014 FIFA World Cup and Rio 2016 Summer Olympics Games in the country. Results showed how it is important to study and characterize the solar resource in the region of interest, based on historic data, to provide the understanding of solar radiation and thus project PV power plants with better performance. Furthermore, AC electrical data show the behavior of active, reactive and apparent powers and the influence of the PV system on the power factor at the local grid utility connection point. Finally, PV power plant performance data (as annual final yield, performance ratio and capacity factor) are also presented and compared with data from PVsyst software simulations. The results over the monitoring period were good considering the specificities of the stadium.

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Performance measurements of monocrystalline silicon PV modules in South-eastern Italy

Cited by 131 publications

References 11 publications

Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)

Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)

Comparative performance investigation of mono- and poly-crystalline silicon photovoltaic modules for use in grid-connected photovoltaic systems in dry climates

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

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